Risk Observability for
Real-time analytics platform, purpose-built for the three lines of defence to analyse, optimise & govern AI Risks in the regulated enterprise
Next-generation AI Risk monitoring integrated with multiple technology stacks
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Audit your readiness & discover newer, emerging risks
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See how it all comes together
With Zupervise, you can now analyse risks across multiple layers of AI: models, training data, inputs & outputs.
Step 1 - Analyse
Identify your AI Risk universe
Discover risks in your current business process design. Enable out of the box AI Risk Controls & manage a balance between AI risk appetite and automation experimentation.
Step 2 - Optimise
Unify AI Risk Data
Foster a culture of AI Risk mitigation and make intelligent & informed risk decisions from a single shared system of record. Govern AI Risks originating from the quality of historical data and that of evaluation & benchmark data-sets.
Step 3 - Govern
Gain Visibility into AI Risk Trends
Delineate accountability and make it easier to place trust in your AI investments with data-driven insights into emerging AI Risks. For each AI Risk, monitor multiple signals, including changes in attributes to be able to forecast a material effect on your risk appetite.
Streamline AI Risk Transparency
Identify AI Risks
Build your own AI Risk and AI controls taxonomy, or re-use our artefacts, templates and libraries to develop forward-looking internal controls.
Breakdown Governance Silos
Single pane of glass dashboard that has source, risk and operational data integration capabilities to improve transparency in automation deployments & outcomes.
Demonstrate Regulatory Compliance
Articulate algorithmic risk provenance to executive stakeholders and regulators on-demand.
news & industry updates
A collection of original content on AI Risk governance, curated news & research.
Let’s do this
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Schedule a meeting with an AI Risk expert to see Zupervise in action